Semantic Similarity

405 papers with code • 8 benchmarks • 12 datasets

The main objective Semantic Similarity is to measure the distance between the semantic meanings of a pair of words, phrases, sentences, or documents. For example, the word “car” is more similar to “bus” than it is to “cat”. The two main approaches to measuring Semantic Similarity are knowledge-based approaches and corpus-based, distributional methods.

Source: Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection

Libraries

Use these libraries to find Semantic Similarity models and implementations

Lightweight Embeddings for Graph Collaborative Filtering

xurong-liang/LEGCF 27 Mar 2024

Graph neural networks (GNNs) are currently one of the most performant collaborative filtering methods.

0
27 Mar 2024

Temporal and Semantic Evaluation Metrics for Foundation Models in Post-Hoc Analysis of Robotic Sub-tasks

jsalfity/task_decomposition 25 Mar 2024

To rigorously evaluate the quality of our automatic labeling framework, we contribute an algorithm SIMILARITY to produce two novel metrics, temporal similarity and semantic similarity.

0
25 Mar 2024

RAmBLA: A Framework for Evaluating the Reliability of LLMs as Assistants in the Biomedical Domain

gsk-ai/rambla 21 Mar 2024

Large Language Models (LLMs) increasingly support applications in a wide range of domains, some with potential high societal impact such as biomedicine, yet their reliability in realistic use cases is under-researched.

1
21 Mar 2024

A Collection of Pragmatic-Similarity Judgments over Spoken Dialog Utterances

divettemarco/pragsim 21 Mar 2024

While there exist measures for semantic similarity and prosodic similarity, there are as yet none for pragmatic similarity.

0
21 Mar 2024

Learning to Rematch Mismatched Pairs for Robust Cross-Modal Retrieval

hhc1997/l2rm 8 Mar 2024

To achieve this, we propose L2RM, a general framework based on Optimal Transport (OT) that learns to rematch mismatched pairs.

6
08 Mar 2024

SAM-PD: How Far Can SAM Take Us in Tracking and Segmenting Anything in Videos by Prompt Denoising

infzhou/sam-pd 7 Mar 2024

Recently, promptable segmentation models, such as the Segment Anything Model (SAM), have demonstrated robust zero-shot generalization capabilities on static images.

3
07 Mar 2024

EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation

MICV-yonsei/EAGLE 3 Mar 2024

Semantic segmentation has innately relied on extensive pixel-level annotated data, leading to the emergence of unsupervised methodologies.

32
03 Mar 2024

The Impact of Word Splitting on the Semantic Content of Contextualized Word Representations

ainagari/splitsim 22 Feb 2024

When deriving contextualized word representations from language models, a decision needs to be made on how to obtain one for out-of-vocabulary (OOV) words that are segmented into subwords.

1
22 Feb 2024

Semantic Textual Similarity Assessment in Chest X-ray Reports Using a Domain-Specific Cosine-Based Metric

sayeh1994/medical-corpus-semantic-similarity-evaluation 19 Feb 2024

Medical language processing and deep learning techniques have emerged as critical tools for improving healthcare, particularly in the analysis of medical imaging and medical text data.

1
19 Feb 2024

SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 14 Languages

semantic-textual-relatedness/semantic_relatedness_semeval2024 13 Feb 2024

Exploring and quantifying semantic relatedness is central to representing language.

23
13 Feb 2024